Instructions to use siyuhsu/openpi_lab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use siyuhsu/openpi_lab with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Model card: drop the results section entirely
Browse files
README.md
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> Piper is 30 Hz. Actions are absolute (G2) or delta-from-start (Piper) joint targets;
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> stepping G2's chunk at 30 Hz would execute it 3× too fast.
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## Results (G2)
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**G2** — offline replay against a live server, 120 frames / 12 episodes:
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| metric | value | threshold |
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| joint MAE | **0.28°** (worst 0.95°) | < 5° |
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| gripper agreement | **99.8%** | > 90% |
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| delta direction cosine | **0.999** | > 0.8 |
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Validated on hardware in four stages — dry-run → ground-truth replay → policy-replay on
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dataset observations → live closed loop — and completes the task in the last stage.
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**Piper** is included as a **worked example**, not as a results claim: a second robot with a
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different arm count, action space and control rate, so the pipeline can be compared against
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something other than G2. No success-rate numbers are reported for it here.
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## Things that will bite you
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* **G2 gripper polarity is inverted between dataset and wire.** In the dataset `1.0` = OPEN,
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> Piper is 30 Hz. Actions are absolute (G2) or delta-from-start (Piper) joint targets;
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> stepping G2's chunk at 30 Hz would execute it 3× too fast.
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## Things that will bite you
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* **G2 gripper polarity is inverted between dataset and wire.** In the dataset `1.0` = OPEN,
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